Stats (3rd Quarter) Flashcards
It is a mathematical concept used to measure the occurrence of statistical events.
Probability
It is the chance of a certain event will occur
or happen.
Probability
Comes from the Latin word “Status” or Italian word “Statistia” or German word “Statistik” or the French word “Statistique”; meaning a political state, and originally meant information useful to the state, such as information about sizes of the population (human, animal, products, etc.)
Statistics
A science that studies data to be able
to make a decision.
Statistics
A science involves the methods of collecting, processing, summarizing and analyzing data in order to provide answers or solutions to an inquiry
Statistics
Statistics as a Tool in Decision-Making it enable us to:
- Characterize persons, objects, situations, and phenomena;
- Explain relationships among variables;
- Formulate objective assessments and comparisons; and,
more importantly - Make evidence-based decisions and predictions.
Provides information only about collected data and does not draw inferences or conclusions about a larger set of data.
Descriptive Statistics
used when one makes a decision, estimates prediction or generalization about a population based on a sample.
Inferential Statistics
The collection or set of units or entities from whom we got the data
Universe
Is a characteristic that is observable or
measurable in every unit of the universe
Variable
Set of all possible values of a variable
Population
A subgroup of a universe or of a population
Sample
The information we asked from the respondents.
Variable
A characteristic that is observable or
measurable in every unit of the universe.
Variable
It is referred to as categorical
variables such as:
sex (male or female),
religion,
marital status,
region of residence,
highest educational attainment,
etc.
Qualitative
____ data answer
questions “what kind.”
Qualitative
Otherwise called as numerical
data, whose sizes are
meaningful.
Quantitative
It answer questions such as
“how much” or “how many”.
Quantitative
____ variables have
actual units of measure.
Quantitative
____ data may be
classified to as discrete or
continuous.
Quantitative
are those data that can be counted that
includes whole numbers or integers,
example: the number of days, the ages
of survey respondents, and the number
of patients in a hospital.
Discrete
are those that can be measured that
includes fractions and decimals,
example. height of a survey
respondent and the volume of some
liquid substance.
Continuous
According to NATURE, ____ is obtained from variables which are in the form of numbers.
Quantitative or numerical data
According to NATURE, ____ is obtained from variables which are in the form of categories,characteristics, names or labels.
Qualitative or categorical data
According to ARRANGEMENT, ____ is the data without any specific order or arrangement. They are referred to as raw data.
Ungrouped data
According to ARRANGEMENT, ____ is the data that are arranged or tabulated and presented in an organizedmanner
Grouped data
According to SOURCE, ____ it is the first-hand information. Example: Data gathered from a survey, where the person who collected the data is the one using it.
Primary data
According to SOURCE, ____ is the second-hand information. Example: Information from newspapers or journals, economics indicators. The data being used are collected by another person or organization.
Secondary data
It uses any or combination of the five senses (sense of sight, touch, hearing, taste and smell) to measure the variable.
Subjective method
____ obtains data by getting responses through a questionnaire.
Objective method
It obtained through the ___________________ by other entities for certain purposes.
use of existing records or data collected
3 Types of interviews conducted for data collection
- Telephone interviews
- Face-to-face interviews
- Computer-assisted personal interviewing (CAPI)
Data presentation (3)
- Textual
- Tabular
- Graphical
Presenting Data in the form of words, sentences and paragraphs.
Textual
Detailed information are given. It involves enumerating important characteristics, emphasizing significant figures and identifying important features of data.
Textual
Numerical values are presented using tables.
Tabular
Information are lost in tabular presentation of data.
Tabular
The usual tabular form of presenting the distribution of the data.
frequency distribution table
A visual representation of data statistics-based results using graphs, plots, and charts.
Graphical
Levels of measurement (4)
Nominal
Ordinal
Ratio
Interval
Measurement arises when we have variables that are categorical and non-numeric or where the numbers have no sense of ordering.
Nominal
This level ordering is important, that is the values of the variable could be ranked.
Ordinal
These scales have no absolute values–all that we can say is that one person is higher or lower in rank without stating how much greater or less.
Ordinal
The data can be categorized and ranked
It tells us that one unit differs by a certain amount of degree from another unit. Can state how much unit differs from another.
Interval
No absolute zero.
Interval
The data can be categorized and ranked.
There is an existence of zero
Ratio
It is how likely something is to happen. “chance”
Probability
It is a way to map outcomes of a statistical experiment determined by chance into numbers.
Random Variable
It is an activity that will produce outcomes, or a process that will generate data. The outcomes have a corresponding chance of occurrence.
Statistical Experiment
It helps model random phenomena
Random Variable
It is used to model outcomes of random processes that cannot be predicted deterministically in advance (but the range of numerical outcomes may, however, be reviewed).
Random Variable
These are random variables that can take on a finite number of distinct values.
Discrete Random Variables
These are random variables that take an infinitely uncountable number of possible values, typically measurable quantities.
Continuous Random Variables
2 Types of Random Variables
Discrete Random Variables
Continuous Random Variables
The collection of information from a sample of individuals through their responses to questions.
Survey
It is a method of systematically gathering information on a segment of the population such as individuals, families, wildlife, farms, business firms, and unions of workers, for the purpose of quantitative descriptors of the attributes of the population.
Sample Survey
Need for Sampling (5):
Cost
Timeliness
Accuracy
Detailed Information
Destructive Testing
A sample often provides useful and reliable information at a much lower cost than a census.
Cost
A sample usually provides more timely information because fewer data are to be collected and processed. This attribute is particularly important when information is needed quickly.
Timeliness
A sample often provides information as accurate, or more accurate, than a census, because data errors typically can ba controlled better in small tasks.
Accuracy
More time is spent in getting detailed information with sample surveys than with censuses.
Detailed Information
When a test involves the destruction of an item, sampling must be used.
Destructive Testing
involves random selection, allowing you to make strong statistical inferences about the whole group. It means every member of the target population has the opportunity to be included in the sample.
Probability Sampling
involves non-random selection based on convenience or other criteria, allowing you to easily collect data. This means that not every member of the population is given the chance to be part of the sample.
Non-probability Sampling
Basic Types of Probability Sampling (5):
- Simple Random Sampling
- Stratified Sampling
- Systematic Sampling
- Cluster Sampling
- Multistage Sampling
is a type of probability sampling in which the researcher randomly selects a subset of participants from a population. Each member of the population has an equal chance of being selected. Data is then collected from as large a percentage as possible of this random subset.
Simple Random Sampling
It is an extension of simple random sampling which allows for different homogeneous groups, called strata, in the population to be represented in the sample. To obtained a stratified sample, the population is divided into two or more strata based on common characteristics.
Stratified Sampling
Elements are selected from the population at a uniform interval that is measured in time, order, or space. There is firstly, a decision on a desired sample size.
Systematic Sampling
It is a probability sampling method in which you divide a population into clusters, such as districts or schools, and then randomly select some of these clusters as your sample.
Cluster Sampling
This is more complex sampling technique which includes
* dividing the population into strata,
* dividing each stratum into clusters, and
* drawing a sample from each cluster using the simple random sampling technique.
Multistage Sampling
Basic Types of Non-probability Sampling (4):
- Accidental Sampling
- Volunteer Sampling
- Purposive Sampling
- Quota Sampling
It is a type of nonprobability sampling in which people are sampled simply because they are “convenient” sources of data for researchers. Under this method, researcher does not take special efforts to select the sample, but simply selects those who are immediately available.
Accidental Sampling
For this type of sampling, participant volunteer rather than being chosen.
Volunteer sampling
pertains to having an expert select a representative sample based on his own subjective judgment.
Purposive Sampling
sample units are picked for convenience but certain quotas (such as the number of persons to interview) are given to interviewers. This design is especially used in market research.
Quota Sampling
Large-scale or small-scale.
Size of the sample
Where respondents are monitored periodically, cross-section, longitudinal, or quarterly.
Periodicity
Descriptive, analytic
Main objective
Mail, face-to-face interviews, e-survey,phone survey, or SMS survey.
Methods of data collection
Individual, household, establishment, farmer, OFW, etc.
Respondents
Ways of Classifying surveys (5)
Size of the sample
Periodicity
Main objective
Methods of data collection
Respondents
A type of observational study design.
Cross-sectional study design
The investigator measures the outcome and the exposures in the study participants at the same time.
Cross-sectional study
Researchers repeatedly examine the same individuals to detect any changes that might occur over a period of time
Longitudinal study
Possible sources of biases in a sample surveys that one should be cautious about (4):
Wording of questions
Sensitivity of the survey topic
Interviewer biases
Non-response biases
Can influence the response enormously
Wording of questions
income, sex, illegal behavior, etc.
Sensitivity of the survey topic
Selecting respondents or in the responses generated because of the appearance and demeanor of the interviewer.
Interviewer biases
Happens when targeted respondents opt not to provide information in the survey.
Non-response biases
Types of survey errors
Sampling Error
Non-sampling Error
It results from chance variation from sample to sample in a probability sample.
Sampling Error
It is roughly the difference between the value obtained in a sample statistic and the value of the population parameter that would have arisen had a census been conducted. Since estimates of a parameter from probability sample would vary from sample to sample, the variation in estimates serves as a measure of sampling error.
Sampling Error
Non-sampling Error
This results if some groups are excluded from the frame and have no chance of being selected.
Coverage error or selection bias
Non-sampling Error
________ ____ arising due to weaknesses in question design, respondent error, and interviewer’s impact on the respondent.
Measurement error
Non-sampling Error
This occurs when people who do not respond may be different from those who do respond
Non-response error or bias
Non-sampling Error (3):
- Coverage error or selection bias
- Non-response error or bias
- Measurement error
